Cardiorespiratory Responses During High Altitude Ascent to 5160m in Nepal: Relationships to Self-reported AMS
Bibliographic record
Abstract
Individuals ascending to high altitude risk developing acute mountain sickness (AMS). The Lake Louise AMS scoring system is a self-reporting tool without quantitative physiological metrics. The purpose of this study was to assess cardiorespiratory acclimatization and AMS severity during an ascent to high altitude. A group of 20 participants trekked to 5160m over nine days in the Nepal Himalaya. Cardiorespiratory variables were measured every morning following one night at each altitude, including oxygen saturation (SpO2; %), heart rate (HR; min-1), pressure of end-tidal (PET)CO2 (Torr) and respiratory rate (RR; min-1). These measures (delta from 1400m) were correlated with AMS scores during ascent at six altitudes (n=120). Correlations with AMS were as follows: SpO2, significant, moderate negative correlation (ρ=-0.35, PETCO2, no significant correlation (ρ=-0.16, P=0.08); RR, significant, weak negative correlation (ρ=0.24, P=0.008). However, an index combining these four variables ((HR/SpO2)*(RR/PETCO2)) vs. AMS revealed a significant, moderate positive correlation (ρ=0.48, P * Indicates faculty mentor
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".